Σχόλια 0

Το κείμενο του εγγράφου

EditorialEpigenetic robotics:modelling cognitive developmentin robotic systemsAction editor:Ron SunLuc Berthouzea,*,Giorgio MettabaNRI-AIST,AIST Tsukuba Central 2,Umezono 1-1-1,Tsukuba 305-8568,JapanbLIRA-Lab,DIST,University of Genova,Viale Causa 13,Genova 16145,ItalyReceived 17 November 2004;accepted 17 November 2004Available online 15 December 20041.IntroductionAccording to Zlatev and Balkenius (2001),thegoal of Epigenetic robotics is to understand,andmodel,the role of development in the emergenceof increasingly complex cognitive structures fromphysical and social interaction.As such,EpigeneticRobotics is an interdisciplinary eﬀort,combiningdevelopmental psychology,neuroscience,androbotics.This still recent ﬁeld is being driven bytwo main,somewhat parallel,motivations:(a) tounderstandthe brainby constructing embodiedsys-tems – the so-called synthetic approach,and (b) tobuild better systems by learning from human stud-ies.While this two-pronged approach has led topromising results (see (Lungarella,Metta,Pfeifer,&Sandini,2003) for a comprehensive review),theseeditors believe that the ﬁeld will beneﬁt froma morerigorous coupling between both components.Pro-posed models should provide a useful explanatorycomponent and contribute to the validation andfurther development of theoretical foundations.The plausibility of a model should be demonstratedby providing possible explanations for the dataavailable and by being accurate in a wide range ofdevelopmentally valid constraints (Berthouze &Ziemke,2003).It is with this focus in mind thatthe four papers of this special issue were selected.2.Papers in this issueAttention,the process whereby a person or sys-tem decides where to look,or what to imitate,is akey component of development.As such,it hasbeen the focus of quite a few contributions in theﬁeld of epigenetic robotics.In this issue,Bjo¨rneand Balkenius aim to propose a cognitive modelof how normal and autistic children deal withforced attention shifts.To test their model,theyconsidered the study of Akshoomoﬀ and Cour-chesne (1992) and Courchesne et al.(1994) in1389-0417/$ - see front matter 2004 Elsevier B.V.All rights reserved.doi:10.1016/j.cogsys.2004.11.002*Corresponding author.Tel.:+81298615369;fax:+81298615841.E-mail address:luc.berthouze@aist.go.jp (L.Berthouze).Cognitive Systems Research 6 (2005) 189–192www.elsevier.com/locate/cogsyswhich both normal and autistic children weretested on a task involving mixed visual and audi-tory stimuli with forced attention shifts.Takingthe stance that a model of autistic disorders shouldhave its basis in a model of normal cognitive devel-opment,Bjo¨rne and Balkenius constructed a gen-eral cognitive model from components developedto model various other cognitive tasks (e.g.,task-switching experiments,visual search in real-timevideo sequences,emotional conditioning).Byusing non task-speciﬁc components,the authorscould focus on the mechanisms of development,rather than on its consequences.The three compo-nents used were:a contextQ system that learnsassociations between stimuli and response basedon reinforcement,a context module that controlsin what context each stimulus-response associationshould be used,and an automation system thatlearns to produce stimulus-triggered contextualshifts.The authors show the model to success-fully replicate human data,with diﬀerencesbetween normal and autistic children accountedfor by the variation of a single parameter describ-ing the inﬂuence of the automation system on thecontext.Keeping in the realm of the cognitive modelingof key developmental mechanisms,Prince and Hol-lich propose a formal perceptual-level model ofsynchrony detection,a form of contingency detec-tion.As discussed by Gergely and Watson (1999)(see also (Gergely,2003),in a previous special issueon Epigenetic Robotics),contingency detection (ageneralized form of synchrony detection) has beenlinked to a vast array of critical cognitive develop-ments (word learning,object interaction skills,emotional self-awareness and control to name justa few).Nadel (2004) for example,showed that con-tingency facilitates early reciprocal imitation,amechanism hypothesized to help the developmentof a sense of agency.What we lack,however,is aformal model of synchrony detection.To measuresynchrony in audio-visual information,Princeand Hollich used an algorithm by Hershey andMovellan (2000) – where synchrony is deﬁned asGaussian mutual information – and extended itto estimate the degree of synchrony.The modelwas tested against ﬁve tasks of increasing complex-ity – from integrating punctuate visual movementsof an object and synchronous audio presentationsof a word,to audio source separation using thecontinuous visual movements of an oscilloscopeas a substitute for facial speech movements – andcompared with data from infant studies (Pickenset al.,1994,Gogate and Bahrick,1998;Hollich,Newman,and Jusczyk,2004).Although experi-mental results showed some notable diﬀerences be-tween systemand infant performance (in particularon the most complex task),the model detectedaudio-visual synchrony at levels similar to thoseof infants,thus suggesting that a perceptually-based model could ground a developmental modelof synchrony detection.The authors conclude witha number of possible future directions,which willcertainly stimulate the development of contin-gency-aware epigenetic robots.The next contribution deals with another criti-cal component of development,imitation.The re-cent discovery of mirror neurons in the monkeyhas received considerable attention from roboticsto neuroscience.Roboticists have quickly adoptedmirror neurons as a do-it-all tool to construct imi-tating systems.Yet,a number of open questionsremain,one of which being:where do mirror neu-rons come from?This is precisely the focus ofBorenstein and Ruppins contribution.Instead ofdesigning a mirror neuron system,they developedevolutionary agents that demonstrate imitativelearning,without explicitly specifying a particularmechanism for imitation.Adaptation wasachieved using a modiﬁed version of Floreanoand Urzelais (2000) adaptation method.Theexamination of the agents emerging characteristics– structure and dynamics of the resulting neuro-controllers – showed that the agents had developeda neural ‘‘mirror’’ device analogous to that ob-served in biological systems:certain neurons wereactive for both observation and execution of a spe-ciﬁc action,and were not active in any other sce-nario.Although the complexity of the scenario islimited by computational considerations,the studydoes suggest a universal and fundamental link be-tween the ability to replicate the actions of othersand the capacity to represent and match others ac-tions.It is interesting that this result is supportedby recent brain imaging studies showing that inhumans such principle is present to a larger extent190 Editorial/Cognitive Systems Research 6 (2005) 189–192than in the monkey (e.g.,general movement versusgoal-directed movements).Finally,Dominey and Boucher conclude this spe-cial issue bydealingwithanother critical issue inepi-genetic robotics,namely,that of demonstrating the‘‘successive emergence of behaviors in a develop-mental progression of increasing processing powerand complexity’’.Language acquisition providesan excellent case-scenario because generative lin-guists have argued for the need of a ‘‘highly pre-speciﬁed’’ grammar (e.g.,Chomsky,1995) whilevarious infants studies have suggested perceptual-level mechanisms to explain meaning acquisition(e.g.,Mandler,1999).The authors adopt a con-struction based approach and propose a biologi-cally and developmentally plausible frameworkbased on three main processes:(a) extraction ofmeaning from the environment using perceptualprimitives.Inparticular,the authors exploit contactinformation,movements and spatial relationships,an idea which has recently received some attentionin the Epigenetic Robotics community (e.g.,Metta&Fitzpatrick,2003);(b) learning mapping betweengrammatical structure and meaning:words areassociated with individual components of eventdescriptions,and grammatical structure is associ-ated with functional roles within scene events;(c)identifying-discriminating between diﬀerent gram-matical structures of input sentences,a step whichrequires a minimum baseline of semantic knowl-edge.The authors present experimental resultsshowing the system successfully progresses fromwords to sentences.Finally,they discuss the exten-sion of this construction framework to spatial rela-tions and attention.Similarly to Bjo¨rne andBalkeniuss contribution,the focus is to show thatnon task-speciﬁc components can be re-used andprovide the basis for the emergence of new behav-ioral functionality,a stepwhichwe hope will receivemore and more attention fromour community.AcknowledgementsThis special issue follows the 4th InternationalWorkshop on Epigenetic Robotics in Genova,Italy,August 2004 (Berthouze et al.,2004),inwhich all but one contributors to this issue partic-ipated.We thank all speakers and participants forinteresting presentations and discussions.Further-more,we thank all reviewers for their help in thepreparation of this issue.The international reviewpanel comprised:Christian Balkenius,Cognitive Science,Lund Uni-versity,Sweden.Luc Berthouze,Neuroscience Research Institute,AIST,Japan.Yiannis Demiris,Intelligent and Interactive Sys-tems,Imperial College,UK.Luciano Fadiga,Department of Biomedical Sci-ences,University of Ferrara,Italy.Paul Fitzpatrick,Computer Science and ArtiﬁcialIntelligence Laboratory,MIT,USA.Philippe Gaussier,Universite´de Cergy-Pontoiseand ENSEA,France.Hideki Kozima,National Institute of Informationand Communications Technology,Japan.Valerie Kuhlmeier,Department of Psychology,Queens University,Canada.Max Lungarella,Department of Mechano-Infor-matics,Tokyo University,Japan.Giorgio Metta,DIST,University of Genova,Italy.Jacqueline Nadel,CNRS,France.Chrystopher Nehaniv,School of Computer Sci-ence,University of Hertfordshire,UK.Christopher G.Prince,Computer Science,Univer-sity of Minnesota Duluth,USA.Maartje Raijmakers,Department of Psychology,University of Amsterdam,Holland.Brian Scassellati,Department of Computer Sci-ence,Yale University,USA.Matthew Schlesinger,Department of Psychology,Southern Illinois University,USA.Gert Westermann,Department of Psychology,Oxford Brookes University,UK.Tom Ziemke,Department of Computer Science,University of Skovde,Sweden.ReferencesAkshoomoﬀ,N.,& Courchesne,E.(1992).A new role for thecerebellumin cognitive operations.Behavioral Neuroscience,106(5),731–738.Editorial/Cognitive Systems Research 6 (2005) 189–192 191Berthouze,L.,Kozima,H.,Prince,C.,Sandini,G.,Stojanov,G.,Metta,G.,& Balkenius,C.(2004).Proceedings of thefourth international workshop on epigenetic robotics (Vol.117).Lund University Cognitive Studies.Berthouze,L.,& Ziemke,T.(2003).Epigenetic robotics –modelling cognitive development in robotic systems (edito-rial).Connection Science,15(4),147–150.Chomsky,N.(1995).The minimalist program.Cambridge,MA:MIT Press.Courchesne,E.,Townsend,J.,Akshoomoﬀ,N.,Saioh,O.,Yeung-Courchesne,R.,Lincoln,A.,et al.(1994).Impair-ment in shifting attention in autistic and cerebellar patients.Behavioral Neuroscience,108(5),848–865.Floreano,D.,& Urzelai,J.(2000).Evolutionary robots withon-line self-organization and behavioral ﬁtness.NeuralNetworks,13,431–443.Gergely,G.(2003).What should a robot learn from an infant.mechanisms of action interpretation and observationallearning in infancy.Connection Science,15(4),191–210.Gergely,G.,& Watson,J.(1999).Early social cognition:Understanding others in the ﬁrst months of life (pp.101–136).Mahwah,NJ:Lawrence Erlbaum.Gogate,L.,& Bahrick,L.(1998).Intersensory redundancyfacilitates learning of arbitrary relations between vowelsounds and objects in seven-month-old infants.Journal ofExperimental Child Psychology,69,133–149.Hershey,J.,& Movellan,J.(2000).Advances in NeuralInformation Processing Systems (Vol.12,pp.813–819).Cambridge,MA:MIT Press.Hollich,G.,Newman,R.,& Jusczyk,P.(2004).Infants use ofvisual information to segment speech in noise.ChildDevelopment.Lungarella,M.,Metta,G.,Pfeifer,R.,& Sandini,G.(2003).Developmental robotics:a survey.Connection Science,15(4),151–190.Mandler,J.(1999).Language and Space (pp.365–384).Cam-bridge,MA:MIT Press.Metta,G.,& Fitzpatrick,P.(2003).Better visionthrough manipulation.Adaptive Behavior,11,109–128.Nadel,J.(2004).Early imitation and the emergence of a senseof agency.Proceedings of the fourth international workshopon epigenetic robotics (Vol.117,pp.15–16).Lund UniversityCognitive Studies.Pickens,J.,Field,T.,Nawrocki,T.,Martinez,A.,Soutullo,D.,& Gonzalez,J.(1994).Full-term and preterm infantsperception of face–voice synchrony.Infant Behavior andDevelopment,17,447–455.Zlatev,J.,& Balkenius,C.(2001).Introduction:Why epige-netic robotics.Proceedings of the ﬁrst international workshopon epigenetic robotics (Vol.85,pp.1–4).Lund UniversityCognitive Studies.192 Editorial/Cognitive Systems Research 6 (2005) 189–192